Rafat - 7 months ago 65
Python Question

# How to compare between two numpy arrays of different size and return the index column with common elements?

For obvious reasons I have two numpy arrays of different size one with an index column along with x y z coordinates and the other just containing the coordinates. (please ignore the first serial no., I can't figure out the formatting.) The second array has less no. of coordinates and I need the indexes (atomID) of those coordinates from the first array.

Array1 (with index column):

serialNo. moleculeID atomID x y z

1. 1 1 2 0 7.7590151 7.2925348 12.5933323

2. 2 1 2 0 7.123642 6.1970949 11.5622416

3. 3 1 6 0 6.944543 7.0390449 12.0713224

4. 4 1 2 0 8.8900348 11.5477333 13.5633965

5. 5 1 2 0 7.857268 12.8062735 13.4357052

6. 6 1 6 0 8.2124357 12.1004238 14.0486889

Array2 (just the coordinates):

x y z

1. 7.7590151 7.2925348 12.5933323

2. 7.123642 6.1970949 11.5622416

3. 6.944543 7.0390449 12.0713224

4. 8.8900348 11.5477333 13.5633965

The array with the index column (atomID) has the indexes as 2, 2, 6, 2, 2 and 6. How can I get the indexes for the coordinates that are common in Array1 and Array2. I expect to return 2 2 6 2 as a list and then concatenate it with the second array. Any easy ideas?

Update:

Tried using the following code, but it doesn't seem to be working.

import numpy as np

a = np.array([[4, 2.2, 5], [2, -6.3, 0], [3, 3.6, 8], [5, -9.8, 50]])

b = np.array([[2.2, 5], [-6.3, 0], [3.6, 8]])

print a
print b

for i in range(len(b)):
for j in range(len(a)):
if a[j,1]==b[i,0]:
x = np.insert(b, 0, a[i,0], axis=1) #(input array, position to insert, value to insert, axis)
#continue
else:
print 'not true'
print x

which outputs the following:

not true
not true
not true
not true
not true
not true
not true
not true
not true
[[ 3. 2.2 5. ]
[ 3. -6.3 0. ]
[ 3. 3.6 8. ]]

but expectation was:

[[ 4. 2.2 5. ]
[ 2. -6.3 0. ]
[ 3. 3.6 8. ]]

Using a list instead of array for the values of np.insert did the trick.

import numpy as np

a = np.array([[4, 2.2, 5], [2, -6.3, 0], [3, 3.6, 8], [5, -9.8, 50]])

b = np.array([[2.2, 5], [-6.3, 0], [3.6, 8]])

print a
print b
x = []

for i in range(len(b)):
for j in range(len(a)):
if a[j,1]==b[i,0]:
x.append(a[j,0])
else:
x = x
print np.insert(b,0,x,axis=1)

which would output:

[[ 4.   2.2  5. ]
[ 2.  -6.3  0. ]
[ 3.   3.6  8. ]]